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Amalia Lærke Kjær Heltø,1,2 Emilie Vangsgaard Rosager,1,2 Martin Aasbrenn,3 Cathrine Fox Maule,4 Janne Petersen,4,5 Finn Erland Nielsen,1 Charlotte Suetta,3 Rasmus Gregersen1,4,5 1Department of Emergency Medicine, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark; 2Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; 3Department of Geriatrics and Palliative Medicine, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark; 4Center of Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark; 5Section of Biostatistics, Department of Public Health, University of Copenhagen, Copenhagen, DenmarkCorrespondence: Amalia Lærke Kjær Heltø, Bispebjerg and Frederiksberg Hospital, Department of Emergency Medicine, Ebba Lunds Vej 40A, Building 67, 2. floor, Copenhagen, NV, 2400, Denmark, Tel +45 60654575, Email amalia.laerke.kjaer.heltoe.01@regionh.dkPurpose: Over coming decades, a rise in the number of short, acute hospitalizations of older people is to be expected. To help physicians identify high-risk patients prior to discharge, we aimed to develop a model capable of predicting the risk of 30-day mortality for older patients discharged from short, acute hospitalizations and to examine how model performance changed with an increasing amount of information.Methods: This registry-based study included acute hospitalizations in Denmark for 2016– 2018 lasting ≤ 24 hours where patients were permanent residents, ≥ 65 years old, and discharged alive. Utilizing many different predictor variables, we developed random forest models with an increasing amount of information, compared their performance, and examined important variables.Results: We included 107,132 patients with a median age of 75 years. Of these, 3.3% (n=3575) died within 30 days of discharge. Model performance improved especially with the addition of laborat

Purpose: Over coming decades, a rise in the number of short, acute hospitalizations of older people is to be expected. To help physicians identify high-risk patients prior to discharge, we aimed to develop a model capable of predicting the risk of 30-day mortality for older patients discharged from short, acute hospitalizations and to examine how model performance changed with an increasing amount of information. Methods: This registry-based study included acute hospitalizations in Denmark for 2016– 2018 lasting ≤ 24 hours where patients were permanent residents, ≥ 65 years old, and discharged alive. Utilizing many different predictor variables, we developed random forest models with an increasing amount of information, compared their performance, and examined important variables. Results: We included 107,132 patients with a median age of 75 years. Of these, 3.3% (n=3575) died within 30 days of discharge. Model performance improved especially with the addition of laboratory results and information on prior acute admissions (AUROC 0.835), and again with comorbidities and number of prescription drugs (AUROC 0.860). Model performance did not improve with the addition of sociodemographic variables (AUROC 0.861), apart from age and sex. Important variables included age, dementia, number of prescription drugs, C-reactive protein, and eGFR. Conclusion: The best model accurately estimated the risk of short-term mortality for older patients following short, acute hospitalizations. Trained on a large and heterogeneous dataset, the model is applicable to most acute clinical settings and could be a useful tool for physicians prior to discharge., PURPOSE: Over coming decades, a rise in the number of short, acute hospitalizations of older people is to be expected. To help physicians identify high-risk patients prior to discharge, we aimed to develop a model capable of predicting the risk of 30-day mortality for older patients discharged from short, acute hospitalizations and to examine how model performance changed with an increasing amount of information.METHODS: This registry-based study included acute hospitalizations in Denmark for 2016-2018 lasting ≤24 hours where patients were permanent residents, ≥65 years old, and discharged alive. Utilizing many different predictor variables, we developed random forest models with an increasing amount of information, compared their performance, and examined important variables.RESULTS: We included 107,132 patients with a median age of 75 years. Of these, 3.3% (n=3575) died within 30 days of discharge. Model performance improved especially with the addition of laboratory results and information on prior acute admissions (AUROC 0.835), and again with comorbidities and number of prescription drugs (AUROC 0.860). Model performance did not improve with the addition of sociodemographic variables (AUROC 0.861), apart from age and sex. Important variables included age, dementia, number of prescription drugs, C-reactive protein, and eGFR.CONCLUSION: The best model accurately estimated the risk of short-term mortality for older patients following short, acute hospitalizations. Trained on a large and heterogeneous dataset, the model is applicable to most acute clinical settings and could be a useful tool for physicians prior to discharge.

Introduction. Day surgery is increasing, making efforts to improve safe and effective patient turnover of importance. We hypothesised that the introduction of a simple protocol, dictating that anaesthesia should be induced only immediately prior to surgical incision (after surgical preparations) would lead to reduced duration of anaesthesia and postanaesthesia care unit (PACU) stay. Methods. This was a retrospective, single-centre, procedure-specific, explorative feasibility study of patients undergoing anterior cruciate ligament surgery. Timestamps were collected from the electronic patient records within a three-month period before and after introduction of the protocol at the Copenhagen University Hospital, Bispebjerg and Frederiksberg. Clinical outcomes were assessed using the PACU score, based on the modified Aldrete discharge criteria. Results. A total of 44 patients were included in the after-, and 74 in the before-new-protocol group. The protocol was feasible in 44/59 patients (75%). The duration of anaesthesia was significantly reduced: 113 (± 26) versus 135 (± 32), mean difference 22 (11-33) minutes, p < 0.001. The duration of the PACU stay was significantly reduced: 103 (± 54) versus 80 (± 35), mean difference 23 (6-40) minutes, p = 0.01. No difference was observed in clinical outcomes. Conclusions. A simple protocol by which total intravenous anaesthesia was induced immediately prior to surgical incision was feasible, reduced the duration of anaesthesia and yielded a significant reduction in the PACU stay. Further studies with a randomised design are needed to confirm these preliminary findings.

We are grateful for the interest from Hu et al. in our article.1,2 There are different ways to select variables to be selected in a regression model, and there are different preferences among researchers. In general, p-values driven selection of covariates, such as stepwise selection of covariates, are being criticized by an increasing number of analysts, see Lydersen (2015) and references therein.3 Our initial list of candidate preventable risk factors were based on apriori judgment and potential clinical relevance, with use of conceptual frameworks as directed acyclic graphs to identify possible confounders.4 Then, we kept as candidate preventable risk factors only those that were statistically significant in the univariate analysis. For the rest, we have refrained from p-value driven selection of additional covariates. We did also ensure that no pairs of variables in the presented multivariable models were correlated to an extent that would lead to multicollinearity. We regard the step 2 and 3 proposed by you as having the potential to introduce similar problems as stepwise selection of covariates. We agree that the associations between postoperative haemoglobin and albumin and acute kidney injury are interesting. However, inclusion of postoperative albumin in a large multivariable model might have led to collider bias5 as several other covariates and the outcome all could lead to low albumin. Details of postoperative sepsis were unfortunately not available in our data set. We apologize for not clarifying these aspects clearly enough in the original article and once again want to express our gratitude to Hu et al. for their good questions.

Background: The mortality of older patients after early discharge from hospitals is sparsely described. Information on factors associated with mortality can help identify high-risk patients who may benefit from preventive interventions. The aim of this study was to examine whether demographic factors, comorbidity and admission diagnoses are predictors of 30-day mortality among acutely admitted older patients discharged within 24 h after admission. Methods: All medical patients aged ≥65 years admitted acutely to Danish hospitals between 1 January 2013 and 30 June 2014 surviving a hospital stay of ≤24 h were included. Demographic factors, comorbidity, discharge diagnoses and mortality within 30 days were described using data from the Danish National Patient Registry and the Civil Registration System. Cox regression was used to estimate adjusted hazard ratios (aHR) with 95% confidence intervals (CI) for all-cause mortality. Results: A total of 93,295 patients (49.4% men) with a median age of 75 years (interquartile range: 69–82 years), were included. Out of these, 2775 patients (3.0%; 95% CI 2.9–3.1%) died within 30 days after discharge. The 30-day mortality was increased in patients with age 76–85 years (aHR 1.59; 1.45–1.75) and 86+ years (aHR 3.35; 3.04–3.70), male gender (aHR 1.22; 1.11–1.33), a Charlson Comorbidity Index of 1–2 (aHR 2.15; 1.92–2.40) and 3+ (aHR 4.07; 3.65–4.54), and unmarried status (aHR 1.17; 1.08–1.27). Discharge diagnoses associated with 30-day mortality were heart failure (aHR 1.52; 1.17–1.95), respiratory failure (aHR 3.18; 2.46–4.11), dehydration (aHR 2.87; 2.51–3.29), constipation (aHR 1.31; 1.02–1.67), anemia (aHR 1.45; 1.27–1.66), pneumonia (aHR 2.24; 1.94–2.59), urinary tract infection (aHR 1.33; 1.14–1.55), dyspnea (aHR 1.57; 1.32–1.87) and suspicion of malignancy (aHR 2.06; 1.64–2.59).

Background Weight loss after bariatric surgery varies widely between individuals, partly due to genetic differences. In addition, genetic determinants of abdominal obesity have been shown to attenuate weight loss after dietary intervention with special attention paid to the rs1358980-T risk allele in the VEGFA locus. Here we aimed to test if updated genetic risk scores (GRSs) for adiposity measures and the rs1358980-T risk allele are linked with weight loss following gastric bypass surgery.Methods Five hundred seventy six patients with morbid obesity underwent Roux-en-Y gastric bypass. A GRS for BMI and a GRS for waist-hip-ratio adjusted for BMI (proxy for abdominal obesity), respectively, were constructed. All patients were genotyped for the rs1358980-T risk allele. Associations between the genetic determinants and weight loss after bariatric surgery were evaluated.Results The GRS for BMI was not associated with weight loss (beta = -2.0 kg/100 risk alleles, 95% CI -7.5 to 3.3, p = 0.45). Even though the GRS for abdominal obesity was associated with an attenuated weight loss response adjusted for age, sex and center (beta = -14.6 kg/100 risk alleles, 95% CI -25.4 to -3.8, p = 0.008), it was not significantly associated with weight loss after adjustment for baseline BMI (beta = -7.9 kg/100 risk alleles, 95% CI -17.5 to 1.6, p = 0.11). Similarly, the rs1358980-T risk allele was not significantly associated with weight loss (beta = -0.8 kg/risk allele, 95% CI -2.2 to 0.6, p = 0.25).Discussion GRSs for adiposity derived from large meta-analyses and the rs1358980-T risk allele in the VEGFA locus did not predict weight loss after gastric bypass surgery. The association between a GRS for abdominal obesity and the response to bariatric surgery may be dependent on the association between the GRS and baseline BMI.

Introduction: This study aimed to investigate the prevalence of acute kidney injury (AKI) following hip fracture surgery in geriatric patients and to identify predictors for development of AKI with a focus on possible preventable risk factors.Methods: In this retrospective cohort study, we reviewed electronic medical records of all patients above 65 years of age who underwent hip fracture surgery at Copenhagen University Hospital, Bispebjerg, Denmark, in 2018. Acute kidney injury was assessed according to the Kidney Disease Improving Global Outcomes guidelines. Multivariate logistic regression analyses were used to identify independent risk factors for AKI.Results: Postoperative AKI developed in 28.4% of the included patients (85/299). Acute kidney injury was associated with increased length of admission (11.3 vs 8.7 days, P < .001) and 30-day mortality (18/85 vs 16/214, P = .001). In multivariable analysis, higher age (odds ratio [OR]: 1.05, 95% confidence interval [CI]: 1.01-1.08, P = .004), heart disease (OR: 1.78, 95% CI: 1.01-3.11, P = .045), and postoperative blood transfusion (OR: 1.84, 95% CI: 1.01-3.36, P = .048) were associated with AKI. Moreover, a higher postoperative C-reactive protein (199.0 ± 99.9 in patients with AKI, 161.3 ± 75.2 in patients without AKI) and lower postoperative diastolic blood pressure were observed in patients developing AKI.Discussion and Conclusion: Acute kidney injury was common following hip fracture surgery and associated with longer admissions and increased mortality. Patients developing AKI were older and showed several postoperative similarities, including higher C-reactive protein, lower postoperative diastolic pressure, and the need for blood transfusion.

Introduction: Surgical treatment of hip fractures within 24-48 hours decreases morbidity and mortality, but goals for early surgery have not been widely achieved so far. The primary aim of this study was to investigate the feasibility of implementation of a hip call, and the secondary aim was to investigate the effect of the hip call on time for pre-operative preparation and surgery compared to a historical control cohort. Materials and Methods: From March 4, 2019 until June 30, 2019, admission of patients at Copenhagen University Hospital, Bispebjerg, Denmark, with a suspected hip fracture triggered an acute hip call. Key personnel are summoned to secure rapid pre-operative preparation and surgery. The implementation was defined feasible, if ≥ 75% of the patients were ready for surgery within 4 hours and had surgery initiated within 24 hours of hospital arrival. The historical control cohort was patients with hip fractures in the same period in 2018. Results: A total of 128 patients were included in 2019, and 99 in 2018. After implementation of hip call, 83% of patients were ready for surgery within 4 hours. After vs before hip call, 88% vs 51% were operated within 24 hours and 96% vs 79% within 36 hours. Time from admission to surgery (hh:mm) was reduced by mean 10:33 (CI 07:46-13:20), P <.001. Conclusion: The implementation of a hip call was feasible with 83% of patients being ready for surgery within 4 hours, and 88% being operated within 24 hours. Future large-scale studies should clarify potential benefits on clinical outcome.

Background Zonulin is a biomarker of impaired intestinal permeability, which has been associated with various disorders. The primary aim was to study serum zonulin (s-zonulin) in individuals with morbid obesity before and after a conservative weight loss intervention followed by bariatric surgery. The secondary aims were to explore predictors of s-zonulin, and the associations between the changes of the predictors and changes in s-zonulin, and to compare the associations in the two treatment periods. Methods Individuals with morbid obesity were included. Data before any weight loss interventions, after a 6 months' conservative weight loss intervention, and 6 months after bariatric surgery were used. S-zonulin was measured with an ELISA method from Immundiagnostik AB, Bensheim, Germany. Data were analysed with mixed models. Results The mean body mass index was 42.1 kg/m(2)(SD 3.8) at inclusion and was reduced to 38.7 kg/m(2)(SD 3.8) and 29.8 kg/m(2)(SD 3.8) after the conservative treatment and bariatric surgery respectively. S-zonulin was 63 ng/mL (SD 32) at inclusion and was reduced with 19 ng/ml (95% CI 12 to 26,p <0.001) after conservative treatment and 11 ng/ml (95% CI 0 to 21,p = 0.04) after bariatric surgery. At inclusion, s-zonulin was significantly associated with factors including p-glucose (B = 2.21, 95% CI 1.09 to 3.33,p <0.001), c-reactive protein (B = 1.02, 95% CI 0.45 to 1.58,p <0.001) and the intake of proteins (B = 0.23, 95% CI 0.08 to 0.38,p = 0.003) and non-nutritive sweeteners (B = 0.68, 95% CI 0.19 to 1.17,p = 0.007). The reduction in s-zonulin after the conservative weight loss intervention was significantly associated with improvement in diarrhoea (B = 6.6, 95% CI 1.3 to 11.8,p = 0.02), HbA1c (B = 9.7, 95% CI 1.1 to 18.3,p = 0.03), p-glucose (B = 3.5, 95% CI 1.2 to 5.9,p = 0.004) and gamma-GT (B = 0.28, 95% CI 0.09 to 0.47,p = 0.004), but not associated with the change in body mass index (B = 0.9, 95% CI - 1.5 to 3.3,p = 0.46). Concl

Background: Faecal dysbiosis associated with the use of metformin has been conceived as a favourable ("good") dysbiosis and that with intake of non-nutritive sweeteners (NNS) as unfavourable ("bad"). The study aimed to construct an alternative dysbiosis index (ADI) for the separation of the dysbioses into "good" and "bad", and to validate the ADI. Methods: Subjects with morbid obesity were included. Use of NNS and drugs were noted, IBS was classified according to the Rome III criteria and the severity measured with the Irritable bowel severity scoring system (IBSSS). Faecal dysbiosis was tested with GA-Map ™ Dysbiosis test (Genetic Analysis AS, Oslo, Norway). The result was given as Dysbiosis Index (DI) scores 1-5, score > 2 indicates dysbiosis. An ADI was constructed and validated in subjects with IBS at another hospital. Results: Seventy-six women and 14 men aged 44.7 years (SD 8.6) with BMI 41.8 kg/m 2 (SD 3.6) were included. Dysbiosis was associated with the use of NNS and metformin, but not with IBS or IBSSS. An ADI based on differences in 7 bacteria was positively and negatively associated with the "good" metformin dysbiosis and the "bad" NNS dysbiosis respectively. The ADI was also negatively associated with IBSSS (a "bad" dysbiosis). The negative associations between ADI and IBS and IBSS were confirmed in the validation group. Conclusions: The new ADI, but not the DI, allowed separation of the "good" and "bad" faecal dysbiosis. Rather than merely reporting dysbiosis and degrees of dysbiosis, future diagnostic tests should distinguish between types of dysbiosis.